High-resolution large-eddy simulation of the flow over a large wind farm (64 wind turbines) is performed using the HIGRAD/FIRETEC-WindBlade model, which is a high-performance computing wind turbine-atmosphere interaction model that uses the Lagrangian actuator line method to represent rotating turbine blades. These high-resolution large-eddy simulation results are used to parameterize the thrust and power coefficients that contain information about turbine interference effects within the wind farm. Those coefficients are then incorporated into the WRF (Weather Research and Forecasting) model in order to evaluate interference effects in larger-scale models. In the high-resolution WindBlade wind farm simulation, insufficient distance between turbines creates the interference between turbines, including significant vertical variations in momentum and turbulent intensity. The characteristics of the wake are further investigated by analyzing the distribution of the vorticity and turbulent intensity. Quadrant analysis in the turbine and post-turbine areas reveals that the ejection motion induced by the presence of the wind turbines is dominant compared to that in the other quadrants, indicating that the sweep motion is increased at the location where strong wake recovery occurs. Regional-scale WRF simulations reveal that although the turbulent mixing induced by the wind farm is partly diffused to the upper region, there is no significant change in the boundary layer depth. The velocity deficit does not appear to be very sensitive to the local distribution of turbine coefficients. However, differences of about 5% on parameterized turbulent kinetic energy were found depending on the turbine coefficient distribution. Therefore, turbine coefficients that consider interference in the wind farm should be used in wind farm parameterization for larger-scale models to better describe sub-grid scale turbulent processes.
Bibliographical noteFunding Information:
This work was supported by a grant from the Midcareer Researcher Programs of the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT, and Future Planning (grant NRF- 2013R1A2A2A01015333 , NRF-2015R1A2A1A15056182). This work was also supported by the National Research Foundation of Korea (NRF) Grant funded by the Korean Government (MSIP) (No. 2015R1A5A1037668 ). WindBlade is developed with the support by Los Alamos National Laboratory's (LANL) Laboratory Directed Research and Development (LDRD) program ( 20100040DR ), and LANL Institutional Computing (IC) provided high-performance computing resources under w12_windturbines project. The fourth author is supported by Korea Institute of Atmospheric Predictions Systems funded by the Korea Meteorological Administration .
© 2015 Elsevier Ltd.
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Building and Construction
- Mechanical Engineering
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering